Soft Hands represent a departure from traditional robot hand design, which often focuses on precise models and planning of contact points. Instead, our approach emphasizes robustness and safety through the use of soft materials and flexible mechanics. This softness allows us to leverage contact with the environment and use it for effective grasping and manipulation strategies. Our research explores hand design, the integration of sensors in soft hands, and feedback control methods for grasping and in-hand manipulation that take advantage of the hands' morphological properties. Furthermore, we view soft hands as a computational resource that can support robust manipulation behavior generation. This requires a balance between the software that controls the hand and the morphological computation provided by the body, leading to the problem of how to efficiently co-design body and control.
Steffen Puhlmann, Adrian Sieler
The RBO Hand 3 is a highly dexterous and versatile soft hand based on pneumatic actuation. It advances on its predecessor by combining 16 actuated degrees of freedom with intrinsic mechanical compliance in an anthropomorphic design. Special attention was paid to the design of the opposable thumb. The RBO Hand 3 is inherently safe and highly robust for externsive real-world experimentation. It closely replicates the functioning of its human counterpart to facilitate transfer of insights to human dexterity, and it is capable of dexterous grasping and manipulation
The RBO Hand 3 has been featured on the cover of National Geographic and the Soft Robotics Journal.
If you want to build your own RH3, you are welcome to do so. We have published the entire production process here.
Steffen Puhlmann, Apoorv Vaish
The behavior of a robotic agent is determined by its control program, shape and material composition, as well as external factors from its environment. Both control and morphology affect the behavior and thus must be chosen carefully to ensure robust and general behavior in various operating environments. Thus, given a set of tasks, control and morphology must be considered as one combined aspect in designing soft robots. Moreover, we can divide responsibilities into morphology and control simultaneously and synergistically to ensure robust behavior in the physical world. This joint programming of morphology and control is called co-design.
The RBO Hand 2 is a hand made from PneuFlex actuators mounted on a flexible, printed scaffold. The hand was developed to investigate the capabilities and limits of hands when relying only on soft, deformable structures. The unique deformability provides several advantageous benefits to robots trying to interact with the environment:
The result of our research are several hand prototypes, which we refer to collectively as Soft Hands. RBO Hand 2 is the latest model and used in our lab for research into grasping strategies.
If you want to build your own, you are welcome to do so! We have published the CAD models for the PneuFlex actuators
Raphael Deimel, Vincent Wall, Steffen Puhlmann
The RBO Hand (published in 2013) was the first soft hand that employed PneuFlex actuators. It uses 3 pairs of parallel and straight PneuFlex actuators. The finger are also partially connected to each other. The hand has a passively bendable rubber sheet acting as a palm in opposition to the fingers.
Raphael Deimel, Vincent Wall
For the control of the pneumatic RBO Hand 2 we had to create our own hardware. We developed the "PneumaticBox", which consists of valve array, a single-board computer, and a custom printed circuit board.
A detailed description of the hard- and software can be found in the Tutorial section.
We develop a set of production processes and a complete design toolchain for soft continuum actuators under the name PneuFlex. The toolchain consists of several components:
We study human grasping under a variety of conditions in order to identify and characterize different grasping strategies. Specially, we are interested in strategies that are robust to be performed under different kinds of impairment, e.g. visual. Our final goal, is to transfer those robust strategies to a robot. In addition to subjects' grasping with their natural hands, we also observe them when they use soft robotic hands such as RBO Hand 2 and Pisa/IIT Hand. Our goal is to leverage their intuition in grasping to understand how robotic hands can be controlled and evaluate the transfer of their strategies to robotic hands.
Our approach to grasping is motivated by the fact that humans don't avoid contact with the environment but rather exploit it to generate haptic feedback complementing visual feedback. This exploitation of environmental constraints simplifies the grasping problem by converting a high-dimensional configuration search problem into successive local searches guided by these environmental constraints, such as surfaces or edges.
We are developing algorithms that model the environment as a collection of environmental constraints which can be used to generate reactive feedback plans that lead to robust and reliable grasps.
Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy - EXC 2002/1 "Science of Intelligence" - project number 390523135
German Priority Program DFG-SPP 2100 “Soft Material Robotic Systems” - project number 405033880.